@ -176,3 +176,16 @@ For more infos, refer to the [examples](https://github.com/towhee-io/examples/tr
### Dive deep and customize your training
You can change the [training script](https://towhee.io/text-embedding/transformers/src/branch/main/train_clm_with_hf_trainer.py) in your customer way.
Or your can refer to the original [hugging face transformers training examples](https://github.com/huggingface/transformers/blob/main/examples/pytorch/language-modeling).
# More Resources
- [All-Mpnet-Base-V2: Enhancing Sentence Embedding with AI - Zilliz blog](https://zilliz.com/learn/all-mpnet-base-v2-enhancing-sentence-embedding-with-ai): Delve into one of the deep learning models that has played a significant role in the development of sentence embedding: MPNet.
- [Sentence Transformers for Long-Form Text - Zilliz blog](https://zilliz.com/learn/Sentence-Transformers-for-Long-Form-Text): Deep diving into modern transformer-based embeddings for long-form text.
- [Transforming Text: The Rise of Sentence Transformers in NLP - Zilliz blog](https://zilliz.com/learn/transforming-text-the-rise-of-sentence-transformers-in-nlp): Everything you need to know about the Transformers model, exploring its architecture, implementation, and limitations
- [Training Your Own Text Embedding Model - Zilliz blog](https://zilliz.com/learn/training-your-own-text-embedding-model): Explore how to train your text embedding model using the `sentence-transformers` library and generate our training data by leveraging a pre-trained LLM.
- [The guide to jina-embeddings-v2-base-en | Jina AI](https://zilliz.com/ai-models/jina-embeddings-v2-base-en): jina-embeddings-v2-base-en: specialized embedding model for English text and long documents; support sequences of up to 8192 tokens
- [What Are Vector Embeddings?](https://zilliz.com/glossary/vector-embeddings): Learn the definition of vector embeddings, how to create vector embeddings, and more.
- [Evaluating Your Embedding Model - Zilliz blog](https://zilliz.com/learn/evaluating-your-embedding-model): Review some practical examples to evaluate different text embedding models.
- [Training Text Embeddings with Jina AI - Zilliz blog](https://zilliz.com/blog/training-text-embeddings-with-jina-ai): In a recent talk by Bo Wang, he discussed the creation of Jina text embeddings for modern vector search and RAG systems. He also shared methodologies for training embedding models that effectively encode extensive information, along with guidance o
